Novel imaging techniques in cerebral small vessel diseases and vascular cognitive impairment

    Novel imaging techniques in cerebral small vessel diseases and vascular cognitive impairment Gargi Banerjee, Duncan Wilson, Hans R. J¨ager, David J. Werring PII: DOI: Reference:

S0925-4439(15)00364-6 doi: 10.1016/j.bbadis.2015.12.010 BBADIS 64383

To appear in:

BBA - Molecular Basis of Disease

Received date: Revised date: Accepted date:

23 September 2015 7 December 2015 8 December 2015

Please cite this article as: Gargi Banerjee, Duncan Wilson, Hans R. J¨ ager, David J. Werring, Novel imaging techniques in cerebral small vessel diseases and vascular cognitive impairment, BBA - Molecular Basis of Disease (2015), doi: 10.1016/j.bbadis.2015.12.010

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ACCEPTED MANUSCRIPT Novel Imaging Techniques in Cerebral Small Vessel Diseases and Vascular Cognitive Impairment

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Gargi Banerjee1, Duncan Wilson1, Hans R. Jäger2, David J. Werring1 1

Neurology, 10-12 Russell Square, London WC1B 3EE, UK 2

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UCL Stroke Research Centre, Department of Brain Repair & Rehabilitation, UCL Institute of

Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of

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Neurology and the National Hospital for Neurology and Neurosurgery, London, WC1N 3BG, UK

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Corresponding author:

Professor David J. Werring, UCL Stroke Research Centre, Department of Brain Repair &

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Word count: 6772 (text only)

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Rehabilitation, UCL Institute of Neurology, 10-12 Russell Square, London WC1B 3EE, UK

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ACCEPTED MANUSCRIPT Abstract Dementia is a global growing concern, affecting over 35 million people with a global economic impact of over $604 billion US. With an aging population the number of people affected is expected

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double over the next two decades. Vascular cognitive impairment (VCI) describes cognitive

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impairment caused by various types of cerebrovascular disease including cortical and subcortical infarcts, and more diffuse white matter injury from cerebral small vessel disease. Although VaD is

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traditionally considered to be the second most common form of dementia after Alzheimer’s disease (AD), there is increasing recognition of the vascular contribution to neurodegeneration and dementia. In the vast majority of sporadic late onset cognitive impairment, Alzheimer’s pathology

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coexists with vascular pathology. Moreover, cerebrovascular lesions increase the clinical expression of AD pathology, and white-matter changes may be an early feature of AD. The VaD and VCI concepts are of clinical and research importance because vascular factors may be treatable, to

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reduce disease progression. Indeed, recent data suggest that the “dementia epidemic” has not occurred as predicted, which may be due to improved treatment of modifiable vascular risk factors, for example hypertension or dyslipidaemia. The aim of this review is to highlight the recent advances

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neuroimaging techniques.

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in the understanding of VCI, with a focus on small vessel diseases of the brain as detected by recent

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Introduction Dementia is a global growing concern. Worldwide it affects over 35 million people with a global

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economic impact of over $604 billion US[1]. With an aging population the number of people affected

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is expected double over the next two decades with the economic impact expected to rise over 85%

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[1]. Despite the economic burden of dementia being almost twice that of cancer, it attracts 12 times less funding [1]. Vascular cognitive impairment (VCI) describes cognitive deficits secondary to any type of cerebrovascular disease, including both sporadic and inherited conditions, those affecting cortical and subcortical regions, and those involving large and small cerebral vessels [2, 3]. Vascular

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dementia (VaD) refers to a global severe cognitive impairment due to cerebrovascular disease [2]. Cognitive impairment after stroke is very common: a meta-analysis shows the incidence of dementia

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after stroke is 20% at 6 months [4]. Although VaD is traditionally considered to be the second most common form of dementia after Alzheimer’s disease (AD), there is increasing recognition of the vascular contribution to neurodegeneration and dementia [5, 6]. In the vast majority of sporadic late

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onset cognitive impairment, Alzheimer’s pathology coexists with vascular pathology [7, 8].

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Moreover, cerebrovascular lesions increase the clinical expression of AD pathology [9]. It has also been suggested that white-matter changes may be an early feature of AD [10], consistent with a

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vascular contribution. The VaD and VCI concepts are of clinical and research importance because vascular factors may be treatable, to reduce disease progression. Indeed, recent data suggest that the “dementia epidemic” has not occurred as predicted [11], which may be due to improved

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treatment of modifiable vascular risk factors, for example hypertension or dyslipidaemia [12].

Historical perspective and evolving concepts of vascular cognitive impairment A vascular basis to dementia was suggested as long ago as 255 BC by Herophilus [13]. The term “vascular dementia” first arose in the 17th century, hypothesized to be caused “…by a failure of the influx of blood to the brain…” [13]. During the 18th and 19th centuries it was believed vascular congestion was the cause of dementia and blood-letting was a common treatment [13]. In the early 20th century, Pierre-Marie, Binswanger, Fischer and Alzheimer described vascular changes (including lacunes, état crible with perivascular space enlargement, white matter disease and cerebral amyloid angiopathy), providing early evidence of a vascular basis to cognitive impairment; Alzheimer also described parenchymal amyloid senile plaques, the hallmark of AD [14].

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ACCEPTED MANUSCRIPT In the 1970s and 1980s, increasing access to neuroimaging – first computed tomography (CT) and then MRI – led to visualization of cerebral infarcts and white matter changes in patients with VCI in life [15] . It was shown that multiple infarcts (related to occlusion of large arteries) were associated

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with VCI and VaD [15]. Initially, large infarcts were considered the key mechanism: a pathological

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study suggested that an infarct volume of greater than 100mls was associated with cognitive impairment [16]. However, subsequent studies showed similar effects even from small infarcts

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(<15mls), which co-existed with a significant burden of diffuse white matter hyperintensities, suggesting that small vessel disease may play an important role [17, 18]. Strategic single infarcts were also found to cause characteristic cognitive deficits: for example, occlusion of the anterior

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communicating artery is associated with amnesia and personality change [19], while infarction of the angular gyrus consistently causes alexia, agraphia, and Gerstmann's syndrome [20]. A comprehensive list of topographical locations of the large vessel infarcts associated with dementia is

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included in the operational imaging definitions of the NINDS AREN criteria; this operational definition also includes infarcts related to small vessel disease [21]. “Silent” cerebral infarction, mainly related to deep small vessel occlusion, was also associated with the risk of post-stroke

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dementia [22]

A small vessel basis for VCI was suggested in 1968, when Miller Fisher noted that a high burden of

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lacunes was associated with cognitive decline [23]. With the increased availability of neuroimaging, it subsequently became clear that VCI (often in association with presumed AD pathology) could progress even without the accrual of new cerebral infarcts, and that white matter abnormalities

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were extremely prevalent [24, 25]. This led to increasing recognition of the role of small vessel disease (including not only lacunes in the basal ganglia and deep white matter, but also more diffuse lesions in the white matter, often termed leukoaraiosis) [26]. This led to the concept of subcortical VCI (SVCI). Currently, cerebral small vessel disease is recognized as the key mechanism of VCI, with an important synergy with neurodegeneration [27]. In particular advances in MRI have allowed better visualization of the consequences of SVD. The associations of cerebral microbleeds and “microinfarcts” with dementia [28, 29], as well as recognition of impaired amyloid clearance and coexistence of cerebral amyloid angiopathy (CAA) in AD [30] have led to an appreciation that AD and VCI are at the ends of a spectrum where the vast majority of late onset sporadic dementias are caused by ‘mixed’ vascular and neurodegenerative pathology (Figure 1) [31].

The aim of this review is to highlight the recent advances in the understanding of VCI, with a focus on small vessel diseases of the brain as detected by recent neuroimaging techniques. We will focus

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ACCEPTED MANUSCRIPT on imaging markers for small vessel disease and their relationship with cognition, and also discuss

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potential pathophysiological mechanisms.

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Figure 1: Schematic demonstrating how amyloid and non-amyloid related cerebrovascular small vessel diseases may interact in order to produce clinical syndromes. Green line indicates conditions in which arteriolosclerosis is present; yellow line conditions in which Aβ1-42 burden is relevant; grey line for where vascular Aβ1-40 plays a role.

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AD / CAA associated cognitive impairment

AD

Alzheimer’s disease

ApoE

Apolipoprotien E

CAA

Cerebral Amyloid Angiopathy

ICH

Intracerebral Haemorrhage

VCI

Vascular Cognitive Impairment

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Amyloid beta

ApoE ε4 associated Capillary level vascular disease

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Aβ

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Abbreviations:

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Overlap AD / VCI

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Parenchymal Aβ1-42 amyloid burden

Arteriolosclerosis burden

6 Amyloid Negative VCI

Vascular Aβ1-40 amyloid burden

CAA ICH subtype ApoE ε2 associated Small arteriolar level vascular disease

ACCEPTED MANUSCRIPT Small Vessel Diseases Cerebral small vessel disease (SVD) describes pathological processes affecting the small arteries,

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arterioles, capillaries and small veins of the brain, from a few hundred microns to a millimeter or so

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[32]. Pathologically, these diseases have been subdivided into six subtypes (Table 1), which can all result in cerebral damage via incomplete and complete necrosis (due to vessel lumen restriction

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with chronic hypoperfusion and acute micro-occlusion respectively), blood brain barrier disruption, local inflammatory processes and oligodendrocyte loss [32].

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Table 1: Classification of small vessel diseases

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Adapted from [32]

Name

1

Arteriolosclerosis

2

Cerebral amyloid angiopathy

Examples (where relevant)

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Subtype

(hereditary and sporadic)

Inherited / genetic small vessel diseases

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CADASIL MELAS

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3

Fabry’s disease

Inflammatory / immunologically mediated Nervous system vasculitides (e.g. SLE, scleroderma, ANCA-associated)

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small vessel diseases

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Venous collagenosis

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Other

Nervous system vasculitides secondary to infection

Post-radiation angiopathy

Abbreviations: CADASIL Cerebral autosomal dominant arteriopathy with subcortical ischaemic strokes and leukoencephalopathy MELAS

Mitochondrial encephalopathy with lactic acidosis and stroke-like episodes

ANCA

Anti-neutrophil cytoplasmic antibody

SLE

Systemic lupus erythematosus

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ACCEPTED MANUSCRIPT Although a part of normal brain ageing, SVDs cause approximately 20% of strokes worldwide and contribute to a number of dementia syndromes, including Alzheimer’s disease (AD), “pure” vascular cognitive impairment (also called subcortical vascular cognitive impairment, SVCI, and vascular

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dementia, VaD) and the increasingly appreciated “mixed” AD/VCI phenotype [27]. In addition to

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cognitive impairment (in particular, deficits in attention, executive function, verbal fluency and set shifting [33]), SVDs are associated with other symptoms of age-related decline including depression,

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urinary incontinence, gait disturbance and pseudobulbar signs, all of which contribute to functional limitations that affect the performance of daily tasks and lead to a loss of autonomy [32].

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Of the SVD subtypes, types 1 and 2 are the most common [32]. Type 1 SVD, “arteriolosclerosis”, has also been called age-related small vessel disease, vascular risk factor associated small vessel disease and hypertensive arteriopathy [32]. A spectrum of pathology is seen, including small vessel

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segmental arterial disorganization, fibrinoid degeneration, lipohyalinosis and evidence of microatheroma [34]. Type 1 SVD is most strongly associated with hypertension, but also with diabetes and ageing, and is believed to be related to other systemic manifestations of small vessel

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damage, such as microvascular renal and retinal dysfunction [32]. Endothelial failure and blood brain

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barrier (BBB) dysfunction have also been hypothesised to play a role in its pathogenesis [35]. Type 1 SVD is thought to be responsible for “silent” and lacunar infarcts, as well as “deep” intracerebral

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haemorrhages [34, 36-38].

Type 2 SVD, cerebral amyloid angiopathy (CAA), is characterised by the deposition of amyloid in the

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small vessels of the brain [39]; although a number of causative amyloid proteins have been identified, sporadic amyloid β CAA is by far the most common [40]; subsequent reference to CAA refers to this sporadic type. In CAA, amyloid β is laid down in the walls of cortical and leptomeningeal arterioles and capillaries, with involvement initially at the abluminal tunica media before progressing through to panmural accumulation [39]. There is associated smooth muscle cell degeneration, vessel wall thickening, luminary narrowing, concentric splitting of the vessel wall (“double-barrelling”), microaneurysm formation, and perivascular microhaemorrhage [41]. These changes have generally been reported to preferentially affect posterior cortical regions, and the extent of the pathological damage can be used to define CAA severity, with the moderate-severe category most strongly associated with clinical symptoms [41]. CAA can also be classified on the basis of which vessels are predominantly involved. CAA type 1 seems to principally affect capillaries, and is associated with the Apolipoprotein E (ApoE) ε4 genotype, whereas CAA type 2 mainly affects arterioles and is associated with ApoE ε2 [39, 40, 42]. As well as its association with cognitive

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ACCEPTED MANUSCRIPT impairment, CAA is also associated with lobar intracerebral haemorrhage [39, 41]; it is this association which allows the non-invasive diagnosis of CAA (i.e. without the need for brain tissue) using the classical and modified Boston Criteria based on a strictly lobar pattern of large or smaller

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haemorrhages (cerebral microbleeds, CMBs) [43, 44]. Ageing and AD are established risk factors for

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CAA [40]; it has an estimated prevalence of 25% of adults over the age of 70 years [41], and is found in over 90% of AD brains at autopsy [39]. The cognitive deficits in CAA cannot simply be attributed to

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AD however; perceptual speed and episodic memory deficits are associated with CAA even after accounting for AD [45], and patients with hereditary forms of CAA often have cognitive impairment

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in the absence of AD pathology [41].

Although it is not possible to directly visualise these cerebral small vessels on neuroimaging in life [32], advances in imaging allow us to identify the brain parenchymal sequelae of SVD. These can be

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correlated with clinical markers of cognition, to give insight into how these small vessel processes

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result in disease.

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Neuroimaging in Cerebral Small Vessel Disease

Magnetic Resonance Imaging (MRI) Many of the more “classical” MRI markers of SVD and their relationship with cognition have been

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extensively discussed elsewhere (lacunar infarcts [46-48], white matter hyperintensities [49-51] and brain atrophy [52-58]), and so will not be considered here. This review will focus instead on more recently identified small vessel imaging markers that have been associated with cognitive impairment, namely cerebral microbleeds (CMBs), enlarged perivascular spaces (EPVS), cortical superficial siderosis (cSS), microinfarcts, and the use of techniques including diffusion tensor imaging (DTI), MR Perfusion imaging with arterial spin labelling (ASL), functional MRI (fMRI) and Positron Emission Tomography (PET). These MRI biomarkers for SVD are of increasing interest for their potential roles in accurate diagnosis and the monitoring of disease progression, including in response to interventions [59]; these markers may allow much smaller sample sizes than clinical cognitive endpoints [59].

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Figure 2:

Examples of more recently identified imaging findings observed in small vessel disease

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[A] Strictly lobar microbleeds in a patient with CAA (type 2 SVD)

[B] Mixed, but predominantly deep, microbleeds in a patient presenting with a spontaneous intracerebral haemorrhage, likely to be representative of arteriolosclerosis (type 1 SVD)

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[C] Cortical superficial siderosis in a patient with CAA (type 2 SVD) [D] Enlarged perivascular spaces in the cortical white matter

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[E] DTI map showing colour coded tract directionality in a patient with ischaemic stroke

Abbreviations:

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[F] PiB amyloid PET (top) and MRI in a patient with extensive white matter hyperintensities and amyloid retention (adapted from [60])

Cerebral Amyloid Angiopathy

DTI

Diffusion Tensor Imaging

MRI

Magnetic Resonance Imaging

PET

Positron Emission Tomography

PiB

11-Carbon based Pittsburgh compound B

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CAA

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C

F

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ACCEPTED MANUSCRIPT Cerebral microbleeds Cerebral microbleeds (CMBs) are radiologically defined as small hypointense lesions visible on paramagnetic-sensitive MR sequences, which often correlate with haemosiderin-laden perivascular

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macrophages observed pathologically [27]. The detection rate of CMB is higher with the more

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recently developed susceptibility weighted imaging (SWI) compared to T2* weighted imaging, which was the first haemorrhage-sensitive sequence introduced into clinical practice [61, 62]. The

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association of CMB with SVD is now clearly recognised [27] and their topography is thought to depend on the underlying small vessel pathology: strictly lobar (cortico-subcortical) CMBs are associated with CAA, whilst deep or infratentorial CMBs are associated with arteriolosclerosis,

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although lobar CMBs may also be present in this group (Figure 2) [63, 64]. CMBs are seen in approximately 24% of the general population, and their prevalence increases with age, affecting 17.8% of those aged 60 to 69 years, and 38.3% of those aged 80 to 99 years [65]. They are found in

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approximately 35% of those with ischaemic stroke and 60% of those with haemorrhagic stroke [66]; in VaD they are thought to have a prevalence of between 65 and 85% [66].

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A number of studies have demonstrated that CMB burden is associated with cognitive performance

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in the healthy elderly, sporadic and hereditary cerebrovascular diseases [28, 67-75]. Executive function appears to be particularly associated with CMB burden, but deficits in global cognition,

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memory, psychomotor speed and attention have also been reported [67-72, 74, 76]. The relationship between CMBs and cognition does not appear to be completely linear, suggesting a possible threshold effect; having 1 or fewer CMBs does not appear to affect cognition [77], whereas

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higher counts or “multiple” CMBs are more consistently associated with deficits [28, 69, 70, 78, 79]. The evidence for an association of cognitive performance with a particular CMB topography is also conflicting. Some studies have shown a strong association with strictly lobar CMBs [28, 69], and others with deep [75, 80, 81] or mixed [67, 78] CMBs. Although most evidence suggests that CMBs relate to cognition, some studies have reported no relationship [77, 82].

The varied associations of CMBs with cognition may be due in part to the non-linear relationship between CMBs and cognition. The studies that did not demonstrate a relationship between CMBs and cognitive performance had relatively low CMB counts [77, 82]; this may also explain the variation in results for cognition by CMB anatomical location. This suggests that overall burden rather than distribution is more relevant to cognition [37, 64]; studies reviewing the association of CMBs with network connectivity [82] and cerebral blood flow measures [83] in cognitively impaired patients only demonstrate a relationship at high CMB counts, which also supports this concept. Increasing CMB burden may therefore reflect more severe SVD. 12

ACCEPTED MANUSCRIPT Enlarged Perivascular Spaces Perivascular spaces (PVS), also called Virchow-Robin spaces, type 3 lacunes and état crible, describe the potential space between the outer aspect of a vessel wall and the brain parenchyma [27, 84].

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They are believed to be extensions of the extracerebral fluid space and are usually microscopic and

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not visualised on imaging [27]. Enlargement of these spaces so that they can be easily seen as dilated on MRI (EPVS – Figure 2) may be pathological, and has been found to be associated with a

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number of other SVD markers, including white matter hyperintensities (WMH) and lacunes [27]. Visualisation of PVS increases with magnetic field strength and higher image resolution and quantification has been achieved with 7T MRI [85]. It has been hypothesised that enlargement of

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this space is a reflection of impairments in the drainage of interstitial fluid in the brain, which is of particular relevance to SVDs thought to be secondary to “protein elimination failure angiopathies” such as CAA and CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and

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Leukoencephalopathy) [84]. The topography of EPVS may relate to the underlying arteriopathy. In CAA, EPVS in the centrum semi-ovale (CSO-PVS) are common and associated with cortical superficial siderosis [86]; EPVS in the whole white matter (WM-PVS) are associated with strictly lobar

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microbleeds [87, 88]. Furthermore EPVS in the basal ganglia (BG-PVS) do not appear to be associated

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arteriolosclerosis [87, 88].

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with CAA [86], but are associated with age, hypertension and WMH, and thus may reflect

There is a higher EPVS burden in those with AD and mild cognitive impairment (MCI) than controls [89, 90]. EPVS burden in VaD appears to be greater than that in other forms of dementia, such as

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FTD and AD [91, 92]. In the healthy elderly, EPVS burden was associated with an increased risk of incident dementia, with the highest degree of WM-EPVS conferring a hazard ratio of 9.8 (95% CI 1.7 – 55.3), and the highest degree of BG-PVS resulting in a hazard radio of 5.8 (1.2 – 28.4) [93]. Another study in the healthy elderly found that EPVS scores correlated significantly with poor performance in tasks of non-verbal reasoning and general visuospatial ability [94]. Hippocampal PVS however are not associated with WMH [94] or changes in cognition [95]. Despite these clear associations in the healthy elderly, some of the associations of EPVS in SVD are conflicting. WM-EPVS burden is associated with poor cognitive performance in CADASIL [96], but a study of patients with TIA and ischaemic stroke found no relationship between EPVS severity and deficits in any cognitive domain [97]. These findings may, in part, be explained by the association of EPVS with lacunar but not cortical strokes [98]; in this cohort only 30% had a lacunar stroke syndrome [[97].

Although EPVS do seem to be a marker of SVD and not simply brain aging, they remain non-specific, having also been described in other conditions such as multiple sclerosis and myotonic dystrophy 13

ACCEPTED MANUSCRIPT [98]. The anatomical relevance of EPVS remains unclear, especially given that BG-PVS and CSO-PVS correlate strongly with one another [98], and the exact nature of the perivascular drainage pathways and impact on EPVS are yet to be elucidated. Further work is necessary in defining the cognitive

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deficits observed, both in terms of absolute scores and domain-specific performance; there may be

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advantages to investigating this in a clearly defined group, for example those with WMH or lacunar

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stroke.

Cortical superficial siderosis

Cortical superficial siderosis (cSS) describes linear deposits of haemosiderin along the subpial space

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and underlying cortical convexities. cSS is often a distinct haemorrhagic manifestation (in addition to intracerebral haemorrhage and CMBs) of CAA (Figure 2) [99, 100], but may have many other causes

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[99]. Recently, cSS has been found in patients with AD-related cognitive impairment (ADCI) and those with SVCI and amyloid-β on PET (using the ligand PiB - Pittsburgh compound B), but not in PiB negative SVCI, raising the possibility that cSS may have implications in mixed AD/SVCI patients [101].

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There were no differences between the cSS and non-cSS groups in cognitive score (which may have

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been difficult to establish given the small number of patients with cSS); the only differences between these groups were in PiB binding, microbleed distribution and ApoE genotype, all of which were in

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keeping with a hypothesized association between CAA and cSS [101]. cSS can be subdivided into focal and disseminated, depending on the number of sulci affected (≤3 versus >3)[102]. Although this distinction is arbitrary, it does seem to have biological relevance for future intracerebral haemorrhage (ICH) risk in CAA, so disseminated cSS might reflect more severe bleeding-prone

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arteriopathy [42]. Whilst cognitive impairment was associated with disseminated cSS, the significance of this association was lost after adjusting for other markers of CAA severity suggesting that cognitive impairment may simply be associated with severe CAA rather than cSS itself [102].

The prevalence of cSS is higher in memory clinic cohorts than the general population, but not as high as seen in CAA [101, 103]. A study in a memory clinic cohorts found that cSS was associated with a poorer MMSE score and higher white matter burden (but unfortunately did not include WMH as a covariate in the multivariable logistic regression) [104]. Another study in a memory clinic cohort again found that a lower MMSE score was associated with cSS, but this appeared to be driven by AD diagnosis rather than anything else [103].

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ACCEPTED MANUSCRIPT Microinfarcts Microinfarcts are usually defined as microscopic ischaemic lesions that are invisible to the naked eye [105, 106]. Histopathologically, they are described as areas of neuronal loss and demyelination,

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sometimes with cavitation or a cystic component [105, 107-109]; given the pathological similarities

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with larger “macroinfarcts”, they are presumed to occur as the result of ischaemia [107]. Quoted sizes range from 50µm to 5mm [105] (this has been proposed to relate to the diameter of the

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occluded vessel [110]); they are very common in ageing, having been demonstrated in between 16 and 46% of an unselected elderly population [107]. Neuropathological studies have shown a link between microinfarcts and cognitive impairment, with deficits in perceptual speed, semantic

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memory and episodic memory [111]. A pooled analysis of neuropathological data from prospective community based studies demonstrates those with microinfarcts are more likely to have dementia (OR 2.31; 95% CI 1.40 to 3.82) [107]. Microinfarcts seem to be particularly common in VaD (62%

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weighted average), but are also seen in those with AD (43% weighted average), mixed AD and vascular disease (33% weighted average), as well as older subjects without dementia (22% weighted

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average) [105].

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Microinfarct location also supports an association with ischaemia, with increased numbers in borderzone areas of the brain that are particularly susceptible to intermittent hypoperfusion [105].

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Microinfarct topography may also be relevant to the underlying arteriopathy; one study demonstrated that cortical microinfarcts are associated with CAA, whilst subcortical microinfarcts were associated with hypertension (in particular, those in the putamen) [107]. A critical limitation of

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these studies is how microinfarct burden is approximated; it is likely that microinfarct burden measures, even in neuropathological studies, are underestimates, making it difficult to draw firm conclusions about the exact nature of the correlation between microinfarcts and cognition [107, 112].

The ability to identify microinfarcts in vivo could hugely increase our understanding of how they relate to cognition, as well as their extent and anatomical distribution. This has been limited to date by imaging sensitivity: conventional MR uses field strengths of 1.5 or 3 Tesla and can only resolve lesions larger than approximately 1mm3 [107]. Scanning at higher field strengths can improve this spatial resolution [107]. Recently imaging with 7 Tesla (7T) has allowed microinfarcts to be visualised, both in vivo [113-116] and post mortem [110, 114]. Post-mortem 7T imaging demonstrated a high cortical microinfarct (CMI) burden in those with VaD and AD with CAA when compared with controls [110]. Interestingly, the evidence for CMI in AD is conflicting, with one study reporting a higher CMI burden independent of CAA [110] and another showing a better correlation 15

ACCEPTED MANUSCRIPT between CMI and AD than between CMI and CAA [115]; however, a recent third study demonstrated no association at all between CMI and AD [116] . All studies seem to report fewer microinfarcts than anticipated [112], which may explain some of the inconsistencies observed. More recently, 3 Tesla

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(3T) MRI has also been used to identify microinfarcts, both in the healthy elderly [117] and

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populations with cognitive impairment [29, 118]. CMIs identified on 3T imaging were most likely to be seen in VaD, correlated with MMSE score, in particular deficits in language and visual

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construction [29]. Although 7T MR improves resolution to allow visualization of large microinfarcts, these are still much larger than the average microinfarct, so it is likely that the vast majority of these lesions are still being missed [119]. Larger studies with pathological correlation are needed to further

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validate the use of microinfarcts in SVD and cognition.

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Diffusion Tensor Imaging Measures

Diffusion tensor imaging (DTI – Figure 2) is an MRI based technique designed to detect ultrastructural tissue damage through measures of water diffusion [120, 121]. The most common

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measures are fractional anisotropy (FA) and mean diffusivity (MD), both of which are based on the

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principle that myelin and axonal membranes in tracts promote diffusion in a single direction [122]. FA describes the directionality of diffusion, whereas MD is a measure of diffusion averaged in all

[122].

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spatial directions; thus damage to tract structures results in a decrease in FA and an increase in MD

There has been extensive work on DTI in SVDs and cognition, with a body of the initial work

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performed in CADASIL, a genetic SVD due to mutations in the NOTCH3 gene, and in which patients develop recurrent strokes and progressive cognitive decline [121]. It had been noted that disease manifestation in CADASIL was highly variable, with clinical severity poorly correlated with white matter disease burden and progression, even in the absence of ischaemic events [123]. In a study of CADASIL patients, DTI analysis of areas of increased signal on T2 weighted images showed that diffusion changes correlated with MMSE score, and interestingly a similar pattern of diffusion abnormalities were seen in normal appearing white matter, albeit at a lower intensity [123]. DTI measures have also been shown to correlate both with executive cognitive dysfunction [124, 125], and with subsequent disease progression [121, 126] in these patients.

In age-related SVD, DTI measures were abnormal in ischaemic leukoaraiosis (defined as radiological leukoaraiosis and clinical lacunar stroke) [127], with abnormalities within white matter lesions and normal appearing white matter [122]. DTI measures in ischaemic leukoaraiosis correlated with 16

ACCEPTED MANUSCRIPT cognitive function, whereas T2-weighted white matter changes did not [122], and there was particularly strong correlation with scores of executive function [128]. Another study [129] considered those with subcortical ischaemic vascular disease (SIVD), subdivided into those with

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normal cognition, those with cognitive impairment but no dementia, and those with dementia. This

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found significant differences in FA and MD between those with normal cognition and those with cognitive impairment, both in whole brain white matter and normal appearing white matter [129].

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Furthermore both FA and MD were associated with attention-executive and memory measures [129]. Those with SIVD and cognitive impairment but no dementia had abnormalities of FA and MD across all supratentorial projection, association and commissural fibres, and the severity of damage

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to these tracts was associated with cognitive dysfunction [130]. Deficits in hippocampal MD (but not FA) have also been seen in those with VaD [131]. In addition, when considering DTI measures purported to show axonal damage and demyelination (axial and radial diffusivity respectively), it

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appears that radial diffusivity is a stronger predictor of executive dysfunction than axial diffusivity (although this may be confounded by the strong correlation between radial diffusivity and MD)

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[132].

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There may be a relationship between specific cognitive deficits and tract damage in particular locations; a study of patients aged between 55 and 85 years with small vessel disease shows changes

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in the cingulum bundle were most significantly associated with deficits in verbal memory, whereas those in the frontal white matter were most associated with psychomotor speed [133]. DTI changes in the corpus callosum (in particular the genu and splenium) were found to be most significantly

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associated with global cognitive function [133], but this may be reflective of diffuse hemispheric deep white matter tract damage [134]. Interestingly cognitive deficits in those with SVCI were only correlated with supratentorial DTI abnormalities, whereas motor deficits were associated with both supratentorial and infratentorial abnormalities [135]. This study also found posterior white matter DTI abnormalities were also related to performance in a range of cognitive tests, including those for frontal functioning, which may reflect that these tasks require far wider connectivity than previously thought [135].

It seems that DTI can also be used to differentiate between subcortical ischaemic VaD and other dementia subtypes, based on different anatomical patterns of diffusion tensor change [136-140]. A recent study using DTI in “mixed” dementia (i.e. those with amyloid on PiB-PET imaging, as well as SVD markers) demonstrated that the PiB retention ratio (and thus amyloid burden) had no relationship to white matter network parameters, whereas SVD markers (WMH and lacunes) were

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ACCEPTED MANUSCRIPT associated with both decreased network integration and increased network segregation [138]. These network changes were in turn associated with deficits in attention, language, visuospatial, memory and fronto-executive tasks [138]. Patients with CAA demonstrate reductions in FA in the splenium of

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the corpus callosum and temporal white matter [141] and differences in MD that were correlated

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with pre-ICH cognitive impairment [142]. There is some evidence that traditional vascular risk factors, such as hypertension and diabetes, and amyloid-related vascular risk factors, such as ApoE

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genotype, may have a synergistic effect on white matter microstructure, as measured with DTI parameters [143].

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Given its ability to detect diffusion abnormalities in normal appearing white matter, DTI may be the most accurate method for estimating the true burden of SVD in an individual, reflecting microstructural damage not visible on conventional MRI [135]. Changes in MD and FA were

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detectable at 1-year follow up in a group of patients with lacunar stroke and leukoaraiosis, whereas there were no changes in T2 lesion volume, brain volume, cognition or disability [128]. DTI measures may therefore be a powerful surrogate marker for treatment trials in SVD [59]. One study of

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cognitively normal patients aged 60 or above showed that an increasing number of vascular risk

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factors appeared to be associated with changes in FA but not WMH [144], further supporting the argument that DTI abnormalities are the best correlate of SVD burden, clinical manifestation and

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progression. In patients with CAA, small asymptomatic DWI lesions were shown to result in local DTI abnormalities, suggesting this might be the process by which microinfarcts result in cognitive impairment [145]. DTI metrics may thus reflect a common pathway of microstructural disruption as

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a result of SVD-related brain injury.

MR Perfusion Imaging with Arterial Spin Labelling Arterial spin labelling (ASL) involves the measurement of cerebral blood flow through the direct magnetic labelling of blood water as an “endogenous” tracer, [146]. The two main techniques for labeling blood in the extracranial arteries are continuous labelling (CASL) and pulsed labelling (PASL) the latter being easier to perform with fewer hardware requirements [146]. More recently a third technique, called pseudo-continuous arterial spin labeling (PCASL), has gained popularity and is now the recommended technique for clinical applications [147]. ASL has application in the assessment of large and small vessel disease and can be combined with an acetazolamide challenge to assess vascular reserve [146]. Limitations of the technique include susceptibility to motion artefact, delayed arrival of labelled spins in the presence of marked carotid stenosis and lengthy collateral vessels, and “partial volume effect” [148]). 18

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In older adults without dementia but with a high vascular risk burden, increasing age was associated with reductions in cortical blood flow, which were associated with a poorer cognitive performance;

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in those with a low vascular risk burden, there was no such association [149]. Another small study in

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patients with SIVD and AD found that both groups demonstrated marked cerebral blood flow reductions in the frontal and parietal cortex [148]. In those with SIVD, the burden of subcortical

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white matter lesions correlated with decreases in frontal cerebral blood flow and cortical atrophy [148]. Another ASL study found that subjects with diffuse confluent white matter hyperintensities had mean global and cortical CBF values that were approximately 20% lower than subjects with

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punctiform or early confluent white matter lesions [150]. It will be interesting to see how ASL imaging correlates with tests of cognition, and whether deficits in particular cognitive domains have

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neuroanatomical correlates on ASL imaging.

Functional MRI

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Functional MRI (fMRI) aims to measure brain activity by identifying changes in blood flow and

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oxygenation. Patients with SIVD appear to have differences in the pattern of resting state fMRI activation when compared with healthy controls [151-153]. Furthermore there appear to be

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detectable differences between cognitively normal cerebral SVD cohorts and controls [154]. fMRI has also been used to evaluate how patients with CAA respond to a visual task: patients with CAA have an abnormal BOLD (blood oxygenation level dependent) visual stimulus evoked response with reduced amplitude, prolonged time to peak and prolonged return to baseline [155]. Another study

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of fMRI [156] in patients with CAA used both a motor and a visual task, and found that BOLD responses were only impaired in the visual cortex with low amplitudes associated with higher white matter and microbleed burdens. There was no difference between visual evoked potentials between patients and controls, suggesting that the deficits were in cortical rather than sensory pathways [156].

As with all functional studies in SVD, it is difficult to say whether deficits in activity are due to impaired flow or impaired metabolism, and this remains a limitation of these techniques. However, it may still potentially useful tool, in particular in evaluating fMRI profiles whilst tasks of cognition are performed. In CAA, fMRI of visual evoked responses has particular attraction as a potentially reversible and functionally relevant measure of “vascular health” which could be used to test new treatments in smaller cohorts [157].

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ACCEPTED MANUSCRIPT Positron Emission Tomography (PET) Positron Emission Tomography (PET) imaging has been used in two main ways in the context of SVD and cognitive impairment. Fludeoxyglucose (FDG) PET has been used to identify defects in

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metabolism, and amyloid PET has been used in CAA and to establish amyloid burden in those with

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SVCI.

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FDG-PET

One of the limitations of structural imaging markers of SVD is that many individuals with these markers are asymptomatic, whilst others are not. A measure of functional deficit may thus be a

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more accurate correlate of symptom burden, as well as underlying pathophysiological mechanisms [158]. FDG-PET has shown differences in patterns of hypometabolism between AD and vascular

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cognitive syndromes [158-160]. In VaD, FDG-PET demonstrates scattered areas of focal cortical and subcortical hypometabolism, affecting subcortical areas and primary sensorimotor cortex to a greater extent than AD, and association areas to a lesser extent than that seen in AD [161]. As with

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all functional measures in small vessel disease, interpretation of these results is limited as it is not

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possible to say with confidence whether lower FDG parameters are due to impaired perfusion or

Amyloid-PET

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impaired metabolism, but this remains a promising area for further study.

The development of PET ligands that bind amyloid β has finally allowed the quantification of amyloid

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burden ante-mortem, and this has greatly enhanced understanding in all dementia syndromes. Much of the initial work in this area used 11-Carbon based Pittsburgh compound B (PiB), and now newer 18-Fluorine based ligands (with a longer half-life) promise to make amyloid-PET more clinically accessible.

Amyloid-PET has been particular useful in exploring the complex interaction between amyloidassociated dementias (either AD or CAA-associated cognitive impairment) and VaD syndromes. This is of interest as both amyloid deposition and arteriolosclerosis appear to be age-related phenomena that can result in cognitive disturbances [35, 162]. The AMPETIS study [163] demonstrated the different profiles of subcortical vascular dementia (SVaD) patients who were positive and negative for PiB binding. Of the patients with SVaD, 31% were found to have PiB positivity, and this group were older and with greater hippocampal atrophy, but fewer lacunes, than the “pure” (PiB negative) SVaD group; similar findings were found in a later study [164], which found that 36% of those with 20

ACCEPTED MANUSCRIPT SVaD had PiB positivity and predictors of this were age greater than 75 years, a medial temporal atrophy score ≥3 and ≤5 lacunes. This PiB positive SVaD group also had lower MMSE scores and performed worse on delayed recall tests [163]. Interestingly the PiB distribution tended to be peri-

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rolandic and cerebellar rather than having the occipital distribution seen in CAA, suggesting that the

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SVaD PiB positive group may be pathologically discrete [163]. Another study found a similar proportion of PiB positivity in SVaD patients (33.8%) and found differences in hippocampal and

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amygdala shape that allowed accurate distinction between the PiB positive and negative groups (95.7% sensitivity and 75.6% specificity when hippocampal and amygdala analyses were considered together [165]). In those with PiB positivity and SVaD, PiB ratio appears to be associated with

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memory dysfunction but had no relation with any markers of small vessel disease except lacunes, with which it was negatively associated (r = -0.60, p = 0.017); this study did not find any iterative effects of small vessel disease and PiB burden on cognition [166]. Together these studies suggest

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that the concurrent presence of amyloid pathology changes the cognitive profile of those with SVaD. Further classification of this “mixed” amyloid and SVaD group, as well as comparisons of amyloid deposition patterns and cognitive profile with those with CAA remains an exciting area for future

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work.

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Potential Mechanisms of Disease (Figure 3) Cerebral SVD clearly contributes to cognitive impairment, but the precise mechanisms remain unclear. The overlap between amyloid and vascular pathology has led to new hypotheses describing how the two processes may be linked. There are also new ideas on exactly how these pathologies,

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either together or independently, may result in cognitive disturbances. Amyloid-PET imaging has shown that a significant proportion of SVCI patients have PiB positivity and that the presence of amyloid in SVCI seems to alter the profile of the deficits observed [163-165]. It is difficult to know whether to define this as “mixed AD and arteriolosclerosis”, “AD with CAA”, or CAA alone, as PiB cannot differentiate between parenchymal and vascular amyloid. The “two-hit” vascular hypothesis argues that amyloid deposition and small vessel dysfunction co-exist and interact to cause disturbances in cognition [167]. This cumulative effect of amyloid and vascular damage is supported by the findings of the seminal Nun Study [9], as well as the recent amyloid-PET studies in patients with SVCI [33, 130, 135, 163, 165, 168-173]. An interesting alternative theory is that amyloid deposition can occur as the result of vascular dysfunction, for example as a consequence of a protein

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ACCEPTED MANUSCRIPT Figure 3: Potential mechanisms by which imaging markers of small vessel disease may be linked to disease

cSS

Cortical Superficial Siderosis

DTI

Diffusion Tensor Imaging

EPVS

Enlarged Perivascular Spaces

FDG

Fludeoxyglucose

fMRI

functional MRI

ICH

Intracerebral Haemorrhage

MRI

Magnetic Resonance Imaging

PET

Positron Emission Tomography

WMH

White Matter Hyperintensities

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Cerebral Microbleed

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CMB

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Arterial Spin Labelling

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ASL

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Abbreviations:

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STRUCTURAL

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Loss of microstructural integrity

Outcome

PET

FDG-PET measures

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ASL measures fMRI measures

Impaired cerebral perfusion and vascular reactivity

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Disruption of fibre tracts Neurodegenerative Processes

MRI

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CMB EPVS cSS Microinfarcts ICH DTI measures WMH Amyloid PET Lacunes measures

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Imaging Markers of Small Vessel Disease

FUNCTIONAL

Reduced neuronal function, glial and neuronal death, volume loss

VASCULAR COGNITIVE IMPAIRMENT AND DEMENTIA 23

ACCEPTED MANUSCRIPT elimination failure angiopathy (PEFA) [174]. PEFA describes a process by which proteins become entrapped in the perivascular pathways running alongside cerebral small vessels that act as lymphatic drainage pathways [174]. The observation that patients with recent ischaemic stroke have

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increased PiB retention in their peri-infarct region seems to support this hypothesis [173, 175]. As

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well as the impaired drainage due to the accumulation of proteinaceous material within basement membranes, perivascular drainage is also thought to be impaired with increasing age as arterial walls

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lose their elasticity [174]. The recent discovery of lymphatic vessels within the dural sinuses of the murine brain [176] make this a promising area for future study, and will hopefully assist in expanding

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our relatively dichotomous framework for AD and SVCI.

It has recently been suggested that a summative measure of all SVD-related MRI lesions may be more representative of the overall burden of tissue damage than any individual marker [177]. The

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microstructural disruption caused by these markers may be a common end pathway which causes a loss of connectivity (the “disconnection syndrome”[178]), leading to impairments in cognitive performance. Data from DTI, studies of vascular responses and structural connectivity seem to

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support this [155, 156, 179]. A recent paper [179] compared the structural brain networks of

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patients with CAA without dementia and healthy controls, and found that those with CAA had reductions in global network efficiency, and that this was correlated with higher cortical amyloid

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loads and MRI markers of SVD. This lower global efficiency was also associated with cognitive deficits, particularly in tasks of processing speed, executive function and gait velocity [179]. As well as failures of transmission, it will be interesting to establish whether network disturbances can be

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caused by unwanted noise or aberrant background electrical activity; cortical spreading depression (CSD), a slowly propagating wave of partial depolarisation of brain cells that suppress electrical activity [180]. CSD is also recognised in cerebral large vessel events, including ischaemic stroke and subarachnoid haemorrhage [180, 181]. Moreover, microemboli can trigger CSD [181].

Key to understanding any of these potential mechanisms will be the ability to more sensitively image “micro-SVD”; the currently recognised markers may just be the tip of the iceberg. The relevance of anatomical location would also be clarified by improved imaging especially given mechanisms such as Wallerian degeneration can cause damage at sites distant from the point of injury [41]. In addition, some cortical arterioles supply subcortical white matter as well as the cerebral cortex [182]; this may explain why CAA can cause extensive white matter changes despite being a cortical process, and CADASIL patients with their predominantly subcortical pathology can show cortical

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ACCEPTED MANUSCRIPT thinning [41]. Understanding these mechanisms will be essential for identifying new therapeutic approaches.

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Conclusions

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Our understanding of SVD and its relationship with cognition has expanded in recent years, thanks to rapid advances in imaging technology. Amyloid-PET has provided further proof that amyloid and

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vascular pathologies frequently overlap, and will help clinicians classify cognitive disorders more accurately. This will be essential for further therapeutic trials, as will a standardisation of clinical and radiological nomenclature [27, 183]. This improvement in classification, together with an expanding

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repertoire of MRI biomarkers of SVD (summarised in Table 2), should facilitate the organisation of smaller trials that require shorter follow up [59], all of which should lead to a much-needed

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breakthrough in the treatment of cognitive impairment due to SVD.

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Table 2: Summary of Newer Imaging Markers and Techniques in Vascular Cognitive Impairment

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Abbreviations: ASL Arterial Spin Labelling CMB Cerebral Microbleed cSS Cortical Superficial Siderosis DTI Diffusion Tensor Imaging EPVS Enlarged Perivascular Spaces FDG Fludeoxyglucose fMRI functional MRI ICH Intracerebral Haemorrhage MRI Magnetic Resonance Imaging PET Positron Emission Tomography WMH White Matter Hyperintensities

Relationship with cognition in VCI  Generally associated with cognition in the healthy elderly, sporadic and hereditary cerebrovascular diseases  Deficits reported primarily in executive function, but also global cognition, memory, psychomotor speed and attention  Particularly strong association with higher CMB counts – possible threshold effect

EPVS

  

cSS

  

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Imaging marker / technique CMBs

Higher burden in those with VaD Burden may be associated with cognition in healthy elderly and CADASIL Deficits in non-verbal reasoning and general visuospatial ability Seen in those with amyloid related cognitive impairment (AD, SVCI and PiB positivity) but not SVCI Main clinical manifestation is with transient focal neurological episodes (TFNE) Higher prevalence in memory clinic populations 26

Limitations / Outstanding questions  Exact nature of the relationship between CMBs and cognitive performance – is there a threshold?  Is anatomical distribution (strictly lobar vs deep vs mixed) relevant?  Are there differences in distribution and clinical manifestations in different populations (e.g. East vs West)  Further studies of healthy populations are needed to confirm preliminary findings  No association with cognition in TIA / ischaemic stroke population – are EPVS exclusively a marker of small (and not large) vessel diseases?  What is the role, if any, of EPVS topography?  Any effect on cognition and behaviour remains uncertain  May simply be a marker of CAA severity

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DTI

    

MR Perfusion with ASL



Functional MRI

 

FDG-PET



Amyloid-PET

 



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CR

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

MRI approximations of microinfarct burden likely to remain underestimates Most promising strategy for detection is high field, high resolution MRI

US



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

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

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Microinfarcts

Possibility of specific association of cognitive impairment with disseminated cSS Strong neuropathological evidence for association with cognition, in particular perceptual speed, semantic memory and episodic memory 7T studies show greater cortical microinfarct burden in those with VaD and AD with CAA than controls 3T studies show increased burden in those with cognitive impairment, in particular vascular dementia Association with deficits in language and visuospatial tasks Measures correlate with cognition in CADASIL, ischaemic leukoariosis Attention-executive and memory measures Specific cognitive deficits may be associated with tract damage in particular locations Able to detect abnormalities in normal appearing white matter, with changes detectable over a one year time period Some evidence of cortical blood flow reductions in those with SIVD Difference resting state fMRI in those with SIVD Patients with CAA have abnormal BOLD responses to visual tasks Pattern of hypometabolism may be able to differentiate between AD and vascular cognitive syndromes Allows identification of amyloid positive and negative VCI groups, which may be clinico-pathological discrete entities Association of PiB ratio and memory dysfunction

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

27

 

 

 

Do DTI changes mediate the effects of other SVD markers through microstructural integrity loss Are DTI measures an accurate reflection of microinfarct burden?

Further work is necessary to better understand the relationship between ASL and cognition Are deficits in activity due to impaired flow or impaired metabolism? Are deficits in activity due to impaired flow or impaired metabolism? Further classification of amyloid positive and negative VCI groups necessary – do they have different cognitive profiles?

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Abbreviations

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SC R

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CADASIL CMB CMI CSD CSO-PVS cSS CT DTI DWI EPVS FA FDG fMRI ICH MCI MD MMSE MRI PET PiB PVS SIVD SVaD SVCI SVD TIA VaD VCI WMH WM-PVS

Alzheimer's disease Apolipoprotein E Arterial Spin Labelling Basal Ganglia Perivascular Space Blood Oxygen Level Dependent Cerebral Amyloid Angiopathy Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy Cerebral Microbleed Cortical Microinfarct Cortical Spreading Depression Centrum Semiovale Perivascular Space Cortical Superficial Siderosis Computed Tomography Diffusion Tensor Imaging Diffusion Weighted Imaging Enlarged Perivascular Space Fractional Anisotropy Fludeoxyglucose Functional Magnetic Resonance Imaging Intracerebral Haemorrhage Mild Cognitive Impairment Mean Diffusivity Mini Mental State Examination Magnetic Resonance Imaging Positron Emission Tomography Pittsburgh B Compound Perivascular Space Subcortical Ischaemic Vascular Disease Subcortical Vascular Dementia Subcortical Vascular Cognitive Impairment Small Vessel Disease Transient Ischaemic Attack Vascular Dementia Vascular Cognitive Impairment White Matter Hyperintensity White Matter Perivascular Space

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AD ApoE ASL BG-PVS BOLD CAA

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ACCEPTED MANUSCRIPT Acknowledgements Dr Banerjee receives funding from the Rosetrees Trust. Professor Werring receives research support from the Stroke Association, the British Heart Foundation, and the Rosetrees Trust. Professor Jäger

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has received research support from the Samantha Dickson Brain Tumour Trust and the Brain

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Research Trust. Part of this work was undertaken at UCLH/UCL who received a proportion of funding

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from the Department of Health’s NIHR Biomedical Research Centres funding scheme.

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Vascular cognitive impairment describes deficits secondary to any type of cerebrovascular disease Arteriolosclerosis and cerebral amyloid angiopathy are the most common types of small vessel disease Novel imaging techniques have identified new small vessel disease markers that are associated with cognitive impairment Capturing the different neuroimaging features of small vessel disease (rather then a single marker in isolation) may have the best correlation with cognitive performance

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